Fix cached synapses issue

image_generation_subnet/__init__.py

@@ -5,7 +5,7 @@
 from . import miner
 from . import utils
 
-__version__ = "0.1.10"
+__version__ = "0.1.11"
 version_split = __version__.split(".")
 __spec_version__ = (
     (1000 * int(version_split[0]))

image_generation_subnet/utils/config.py

@@ -121,7 +121,7 @@ def add_args(cls, parser):
             "--loop_base_time",
             type=int,
             help="The base time for the loop to run in seconds.",
-            default=600,
+            default=1800,
         )
 
         parser.add_argument(

image_generation_subnet/validator/forward.py

@@ -47,24 +47,28 @@ def wrapper(*args, **kwargs):
 def get_challenge(
     url: str, synapses: List[ImageGenerating], backup_func: callable
 ) -> List[ImageGenerating]:
+    challenge = None
     for i, synapse in tqdm(enumerate(synapses), total=len(synapses)):
-        if not synapse:
-            continue
-        try:
-            data = synapse.deserialize()
-            with httpx.Client(timeout=httpx.Timeout(60)) as client:
-                response = client.post(url, json=data)
-            if response.status_code != 200:
-                challenge = backup_func()
-            else:
-                challenge = response.json()
-        except Exception as e:
-            bt.logging.warning(f"Error in get_challenge: {e}")
-            challenge = backup_func()
         if challenge:
             synapses[i] = synapse.copy(update=challenge)
         else:
-            synapses[i] = None
+            if not synapse:
+                continue
+            try:
+                data = synapse.deserialize()
+                with httpx.Client(timeout=httpx.Timeout(60)) as client:
+                    response = client.post(url, json=data)
+                if response.status_code != 200:
+                    challenge = backup_func()
+                else:
+                    challenge = response.json()
+            except Exception as e:
+                bt.logging.warning(f"Error in get_challenge: {e}")
+                challenge = backup_func()
+            if challenge:
+                synapses[i] = synapse.copy(update=challenge)
+            else:
+                synapses[i] = None
     return synapses
 
 def get_reward_offline(

neurons/validator/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "1.0.0"
+__version__ = "1.0.1"
 version_split = __version__.split(".")
 __spec_version__ = (
     (1000 * int(version_split[0]))

neurons/validator/validator.py

@@ -508,7 +508,7 @@ def forward(self):
 
         bt.logging.info("Updating available models & uids")
         async_batch_size = self.config.async_batch_size
-        loop_base_time = self.config.loop_base_time  # default is 600 seconds
+        loop_base_time = self.config.loop_base_time
         self.open_category_reward_synapses = self.init_reward_open_category_synapses()
         threads = []
         loop_start = time.time()
@@ -717,7 +717,8 @@ def prepare_challenge(self, uids_should_rewards, model_name, pipeline_type):
                 if info["model_name"] == model_name
             ]
         )
-        batch_size = min(4, 1 + model_miner_count // 4)
+        # batch_size = min(4, 1 + model_miner_count // 4)
+        batch_size = 1
 
         random.shuffle(uids_should_rewards)
         batched_uids_should_rewards = [